Sentence examples for simple model parameters from inspiring English sources

Finally, we determined confidence intervals for the simple model parameters that can be used to further aid in management of the disease.

Despite using only the two electrojet borders and the cross-meridian current, good reproduction of the input data is demonstrated, so that we can conclude that the simple modeling parameters represent a large part of the variation in physical parameters during the events studied.

From this perspective, we have investigated the structures and their mechanical properties from nanoscopic to macroscopic scale of fresh ex-vivo white New-Zealand rabbit Achilles tendon using second harmonic generation (SHG) microscopy, atomic force microscopy (AFM) and tensile tests to provide a "simple" model whose parameters are relevant of its micro or nano structure.

Since we consider a simple model each parameter value represents a wider range of processes and our observation thus implies that both changes in protein concentration as well as cross-talk between signaling pathways can alter the qualitative response to a TGF- β stimulus.

For this reason, Jimenez-Valverde et al. [24] concluded that simple models (fewer parameters, simpler relationships) should be favored over complex ones (more parameters, more complex functions: overfit) for modeling potential invasive distributions.

Except for TWP2 in simple model all the parameters are positively valued by the households and similarly, results from interaction model indicate that all the parameters in both the two models were significantly valued at either 1 or 5 % levels.

The parameters shown are for the simplest model (fewest parameters) that could be fitted without a significant (P = 0·05) increase in residual deviance compared with the best-fit model.

Spatial covariates were also introduced through a simple model linking GPD parameters to latitude, longitude and altitude.

In this simple model, the only parameters necessary to determine the properties of the fitness landscape, such as ruggedness and frequency of local peaks, are the value of k and the difference in altitude between the global peak and the foot, defined as the region in the sequence space where random sequences are located.

The fitting of RFS curves, even in the absence of systemic treatment and even with large sample sizes, poses serious identifiability problems; that is, even a relatively simple model requires more parameters than can be simultaneously and accurately estimated.

Tail-flick latency of thermal hyperalgesia was a well-characterized and simple model with suitable parameters for predicting analgesia in humans, 33– 35 so we recorded the value of TL instead of paw withdrawal latency.